Literature DB >> 23178187

Modeling the effect of changing selective pressures on polymorphism and divergence.

Etam Benger1, Guy Sella.   

Abstract

The most common models of sequence evolution used to make inferences about adaptation rely on the assumption that selective pressures at a site remain constant through time. Instead, one might plausibly imagine that a change in the environment renders an allele beneficial and that when it fixes, the site is now constrained-until another change in the environment occurs that affects the selective pressures at that site. With this view in mind, we introduce a simple dynamic model for the evolution of coding regions, in which non-synonymous sites alternate between being fixed for the favored allele and being neutral with respect to other alleles. We use the pruning algorithm to derive closed forms for observable patterns of polymorphism and divergence in terms of the model parameters. Using our model, estimates of the fraction of beneficial substitutions α would remain similar to those obtained from existing approaches. In this framework, however, it becomes natural to ask how often adaptive substitutions originate from previously constrained or previously neutral sites, i.e., about the source of adaptive substitutions. We show that counts of coding sites that are both polymorphic in a sample from one species and divergent between two others carry information about this parameter. We also extend the basic model to include the effects of weakly deleterious mutations and discuss the importance of assumptions about the distribution of deleterious mutations among constrained non-synonymous sites. Finally, we derive a likelihood function for the parameters and apply it to a toy example, variation data for coding regions from chromosome 2 of the Drosophila melanogaster subgroup. This modeling work underscores how restrictive assumptions about adaptation have been to date, and how further work in this area will help to reveal unexplored and yet basic characteristics of adaptation.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23178187      PMCID: PMC4296563          DOI: 10.1016/j.tpb.2012.10.001

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  41 in total

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2.  Codon-substitution models for heterogeneous selection pressure at amino acid sites.

Authors:  Z Yang; R Nielsen; N Goldman; A M Pedersen
Journal:  Genetics       Date:  2000-05       Impact factor: 4.562

3.  Positive and negative selection on the human genome.

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Review 4.  Molecular phylogenetics: state-of-the-art methods for looking into the past.

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Journal:  Trends Genet       Date:  2001-05       Impact factor: 11.639

5.  Adaptive protein evolution in Drosophila.

Authors:  Nick G C Smith; Adam Eyre-Walker
Journal:  Nature       Date:  2002-02-28       Impact factor: 49.962

6.  A map of human genome variation from population-scale sequencing.

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7.  Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change.

Authors:  Adam Eyre-Walker; Peter D Keightley
Journal:  Mol Biol Evol       Date:  2009-06-17       Impact factor: 16.240

8.  The genomic rate of adaptive amino acid substitution in Drosophila.

Authors:  Nicolas Bierne; Adam Eyre-Walker
Journal:  Mol Biol Evol       Date:  2004-03-24       Impact factor: 16.240

9.  Detecting past positive selection through ongoing negative selection.

Authors:  Georgii A Bazykin; Alexey S Kondrashov
Journal:  Genome Biol Evol       Date:  2011-08-22       Impact factor: 3.416

10.  A population genetics-phylogenetics approach to inferring natural selection in coding sequences.

Authors:  Daniel J Wilson; Ryan D Hernandez; Peter Andolfatto; Molly Przeworski
Journal:  PLoS Genet       Date:  2011-12-01       Impact factor: 5.917

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  3 in total

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Journal:  Biol Lett       Date:  2015-10       Impact factor: 3.703

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Journal:  Genetics       Date:  2016-12-07       Impact factor: 4.562

3.  Senescence and entrenchment in evolution of amino acid sites.

Authors:  A V Stolyarova; E Nabieva; V V Ptushenko; A V Favorov; A V Popova; A D Neverov; G A Bazykin
Journal:  Nat Commun       Date:  2020-09-14       Impact factor: 14.919

  3 in total

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